Bee Phenological Distributions Predicted by Inferring Vital Rates.

Area of Science:

• Ecology
• Entomology
• Climate Science

Background:

• Bee phenology shifts due to climate variation, impacting plant-pollinator interactions.
• Previous studies often used simplified measures of phenological timing.
• Understanding causes of phenological shifts is crucial for conservation.

Purpose of the Study:

• To simultaneously infer interannual shifts in bee phenology, vital rates, and population dynamics.
• To investigate the influence of floral abundance on bee abundance.
• To develop a more comprehensive model of bee phenological responses.

Main Methods:

• Developed a hierarchical Bayesian model for transition rates between life stages.
• Utilized fine-scale abundance time series data for the sweat bee Halictus rubicundus.
• Collected data at the Rocky Mountain Biological Laboratory, Colorado.

Main Results:

• Halictus rubicundus emergence timing was highly sensitive to snowmelt timing.
• Emergence rate, senescence rate, and population size showed minimal interannual variation.
• Floral abundance influenced observed bee abundance.

Conclusions:

• Snowmelt is a critical cue for sweat bee phenology.
• The developed modeling approach can be applied to other bee and flower phenology datasets.
• Improved understanding of pollination interactions through detailed phenological analysis.